Search Results (6,558)

Electric vehicles (EVs) are essential for sustainable urban mobility, coordinating transportation demands with energy distribution networks. However, uncoordinated EV charging neglects trip chain continuity, inducing spatial–temporal congestion and overloading local charging capacities. Thus, effectively guiding EVs is a key problem in mitigating traffic emissions and preventing power grid-side stress. In this paper, a two-stage dynamic routing framework within a traffic–energy coordination architecture is proposed, integrating an AHP–Entropy–TOPSIS model for station selection and an Improved Ant Colony Optimization algorithm for trajectory execution. Using this framework, a series of macro–micro simulations on the Sioux Falls network was conducted alongside a congestion-driven dynamic pricing mechanism. The results indicate that the pricing strategy facilitates spatial load balancing through peak shaving at core nodes. Compared to conventional standard meta-heuristic baselines, this framework reduces average economic costs by 28.9% while ensuring battery safety and limiting indirect carbon emissions. The proposed framework provides a multi-objective navigation solution that prevents cross-layer decision fragmentation, supporting the sustainable development of smart city infrastructure. Full article

Heating, ventilation, and air conditioning (HVAC) systems struggle to maintain optimal thermal comfort because perception is subjective and varies significantly across individuals. Traditional uniform cooling strategies often overlook demographic diversity, leading to inequitable comfort outcomes and inefficient building operations. To address this limitation, this study analyzed a web-based survey of 366 university occupants using a partial proportional odds model with multiple imputation and inverse-frequency weighting. Interaction terms, specifically Age–Activity, Gender–Clothing, and Age–Clothing, were included to assess combined effects that reflect demographic disparities in adaptive capacity. The results show that clothing insulation, activity, age, gender, race/ethnicity, and space type significantly influence thermal responses. Notably, male occupants were more than three times as likely to report feeling too warm (odds ratio [OR] = 3.24), whereas older adults exhibited significantly lower odds of reporting feeling too warm (OR = 0.42). Substantial variation was observed across racial and ethnic groups (ORs ranging from 2.4 to 6.5). These findings highlight the limitations of traditional population-average comfort approaches and provide valuable scientific insights for demand-response-ready HVAC strategies that adjust temperature setpoints dynamically without sacrificing comfort. By offering accurate, real-time estimates across diverse thermal ranges, these occupant-centric models reduce HVAC energy use and associated emissions at the building scale while supporting ancillary services for flexible load shifting and smarter coordination within low-carbon electric grids. Ultimately, incorporating demographic and contextual diversity into building controls reduces unnecessary cooling waste while promoting thermal equity, establishing a human-centric foundation for sustainable built environments. Full article

Global energy de-fossilization requires scalable solutions for extended energy storage and industrial emission reduction. Synthesizing green methane via Power-to-Gas technology offers a viable pathway to store renewable electricity while utilizing captured carbon dioxide. This review evaluates recent advancements in catalytic mechanisms, reactor engineering, artificial intelligence applications, and techno-economic and life cycle assessments of green methane production systems. Analysis shows that advanced reactor configurations effectively manage the exothermic heat of the Sabatier reaction. Furthermore, integrating machine learning algorithms accelerates catalyst discovery and enables dynamic process control under fluctuating renewable energy loads. Economic and environmental assessments indicate that the sustainability of green methane depends strictly on utilizing renewable electricity and sourcing non-fossil carbon. Commercial deployment must focus on improving catalyst stability during transient operations and implementing digital twins to establish green methane as a sustainable carbon backbone for chemical industries. Full article

Biochar is a carbon-rich material produced from biomass pyrolysis whose properties can be tailored for various applications, including soil improvement, water purification, and catalysis. Its light absorption capacity also makes it promising for solar-driven processes like water evaporation. Photothermal membrane distillation (PMD) combines membrane separation with light-induced heating for efficient water purification. Unlike conventional membrane distillation, PMD utilizes light-absorbing materials to enhance vapor pressure and overcome temperature polarization, a common issue in membrane distillation. This study explored the potential of biochars and activated biochars, as filler materials for photothermal membranes, in line with circular economy principles. The mixed matrix membranes were prepared in a single step, via non-solvent induced phase separation starting from a uniform dispersion of the filler in a polyvinylidene fluoride solution. These materials exhibited great heating performance, reaching surface temperature up to 36 °C under a 125 W/m² light source. Increasing the biochar loading up to 15 wt.% resulted in an 85% increase in distillation flux under light irradiation. Full article

This work presents a methodology for the generation of continuous fibre trajectories based on principal stress directions in continuous fibre-reinforced additive manufacturing (CFAM). The material system considered consists of continuous carbon fibre (CCF-1.5K) embedded in a CFC-PA thermoplastic matrix. CFAM enables the deposition of fibres along tailored paths, allowing improved alignment with the load direction, compared to traditional composite manufacturing. In this way, the strong anisotropy of composite materials, typically considered a limitation, is exploited as a design opportunity by aligning fibres with the structural load paths. The proposed approach combines finite element analysis with a path generation procedure, including the computation of principal stress directions, the extraction of streamlines of the principal stress field, and a dedicated post-processing stage aimed at obtaining continuous and manufacturable fibre layouts. The effectiveness of the method is assessed through a finite element-based comparison with conventional fibre configurations, showing an increase in global stiffness of approximately 20% with respect to the best-performing unidirectional layout. In addition, the feasibility of the generated trajectories is demonstrated through printing tests performed on a continuous fibre additive manufacturing system. The results confirm that the proposed methodology enables the generation of physically realizable fibre paths while improving structural performance. Full article

To investigate the bonding performance between Northeast larch (Larix gmelinii) and carbon fiber-reinforced polymer (CFRP) as well as basalt fiber-reinforced polymer (BFRP), this paper systematically analyzes the effects of fiber-reinforced polymer (FRP) type, bonding length, and bonding width on the mechanical behavior of the interface through single shear pull-out tests. A total of 20 FRP-timber specimens were designed for the tests, and their ultimate bearing capacity, failure mode, strain distribution, and load-slip relationship were measured. The results indicate that BFRP exhibits greater ductility, averaging 35.04% higher than CFRP, while CFRP demonstrates significantly higher tensile strength, exceeding BFRP by 83.41%. The failure mode of CFRP specimens primarily involves debonding at the timber-adhesive interface, whereas BFRP specimens mainly exhibit debonding at the FRP-adhesive interface. An increase in bonding width leads to a larger bonding area, resulting in a higher ultimate load capacity. However, due to the limitations of effective bonding length, the ultimate load increases rapidly when bonding length is raised from 50 mm to 100 mm, but further increases in length yield diminish returns in load capacity. Strain distribution analysis reveals that the strain in FRP decreases linearly along the bonding length, with peak strain increasing as bonding width decreases. Based on the experimental data, a predictive model for interfacial debonding load capacity was developed, demonstrating good robustness with an average coefficient of determination (R²) of 0.65. This model provides a reliable theoretical reference for evaluating the ultimate load capacity of FRP-reinforced Northeast larch structures, while also offering essential experimental evidence and theoretical support for FRP reinforcement design in Northeast larch wood structures. Full article

Manganese dioxide (MnO₂) modified biochar catalysts derived from biomass and waste polymer feedstocks were synthesized and evaluated as heterogeneous Fenton-like catalysts for solar-driven degradation of Rhodamine B (RhB) in aqueous systems. Biochars produced from maple wood and plastic waste (high-density polyethylene) provided porous carbon matrices with oxygen-rich surface functionalities that enabled effective MnO₂ loading and catalytic activity. Photocatalytic experiments conducted under real sunlight using a solar-collector reactor demonstrated faster RhB degradation compared to a conventional ultraviolet (UV) system, confirming the advantage of solar-driven operation. Complete RhB removal was achieved at initial concentrations of 100–300 ppm, whereas higher dye concentrations (500 ppm) exceeded the catalytic capacity within the tested reaction time. Kinetic analysis revealed catalyst-dependent reaction behaviors, indicating that degradation pathways were strongly influenced by the biopolymer-derived carbon structure and MnO₂ dispersion. Degradation efficiency was correlated with solar irradiance and reactor temperature, with higher UV index conditions enhancing catalytic performance. Reusability tests showed that the catalysts remained active over multiple cycles, although gradual decreases in reaction rates and catalyst recovery were observed. These results demonstrate the potential of biopolymer-derived carbon materials as effective solar-driven catalysts for wastewater treatment applications. Full article

The efficient photocatalytic generation of hydrogen peroxide (H₂O₂) from pure water remains a formidable challenge, primarily due to the rapid recombination of photogenerated electron–hole pairs and insufficient redox potentials inherent in single-component photocatalysts. To address these issues, we designed and synthesized a heterojunction material comprising cadmium sulfide nanoparticles loaded on carbon spheres (CS@CdS). Under conditions utilizing pure water and ambient air, the CS@CdS composite achieves an H₂O₂ production rate of 1305 μmol·g⁻¹·h⁻¹, which is 3.1 and 3.6 times higher than that of pure CdS and CS, respectively, without the need for any sacrificial agents or external oxygen supply. Systematic characterization reveals that CS and CdS form a tightly coupled electronic interface, which significantly accelerates charge carrier separation and effectively prolongs the lifetime of photogenerated carriers, thereby boosting photocatalytic performance. Furthermore, the CS component extends the visible-light absorption range of the composite and functions as an electron acceptor to suppress charge recombination, collectively endowing CS@CdS with enhanced photocatalytic activity. Mechanistic studies indicate that H₂O₂ production over CS@CdS proceeds predominantly via a two-step single-electron oxygen reduction reaction (ORR) pathway. This work offers a viable strategy for constructing CS-based heterojunction photocatalysts for efficient H₂O₂ synthesis. Full article

The sustainable collaborative operation of multi-park integrated energy systems (MPIESs) with shared energy storage (SES) provides a significant pathway for low-carbon transition, renewable energy utilization, and energy efficiency improvement, thereby supporting regional energy sustainability. However, realizing this potential faces challenges, including source-load uncertainty, conflicts of interest among multiple entities, and the need for privacy-preserving distributed coordination. To address these issues, this paper proposes a distributed robust energy management strategy for MPIESs with SES, which is decomposed into two sub-problems. In the first sub-problem, a robust optimization model incorporating the SES leasing mechanism is established to handle the uncertainties of photovoltaic (PV) generation and loads. In the second sub-problem, a cooperative game model based on Nash bargaining theory is constructed to fairly allocate the cooperative surplus among participating parks. The alternating direction method of multipliers (ADMM) is employed to solve the overall model in a distributed manner, and enabling collaborative scheduling with limited information exchange. Case studies indicate that the proposed strategy reduces the total system operating cost by 17.57% compared to the independent operation mode. The benefit allocation mechanism achieves Pareto improvement and effectively mitigates the uneven distribution of cooperative surplus among parks. Furthermore, the distributed algorithm converges within 13 iterations in the test case, demonstrating good computational tractability. Consequently, the results verify the effectiveness of the proposed framework in balancing economy, fairness, and robustness, thereby promoting the low-carbon and sustainable operation of regional integrated energy systems. Full article

Accurate characterization of the true tire–pavement contact state is essential for understanding pavement friction; yet conventional texture indicators and nominal contact assumptions cannot directly represent the actual interfacial interaction between rubber and pavement. This study proposes a rapid and non-destructive method for measuring three-dimensional tire–pavement true contact texture under different loads. A materials testing system was used to apply controlled loads to a rubber pad–carbon paper–pavement assembly, and the resulting imprints were combined with three-dimensional laser profilometer data and support-curve-based slicing to determine the real contact area ratio, penetration texture depth, and self-affine fractal dimension. Tests on nine asphalt pavement samples under loads from 5 to 20 kN showed that the real contact area ratio increased with load but remained below 40% at 20 kN. The predicted contact area from the reconstructed 3D texture agreed well with the imprint-based results, with an absolute error not exceeding 2.59%. Penetration texture depth showed a stronger relationship with skid resistance than fractal dimension. The proposed method provides a practical means of capturing effective tire–pavement contact parameters and offers useful inputs for laboratory-based skid resistance evaluation and texture-informed friction modeling. Full article

This study presents a novel methodology integrating high-resolution X-ray computed tomography, digital volume correlation and statistical visualisation mapping, to perform microscale observations and correlate delamination fracture mechanisms in heterogeneous materials. To demonstrate the utility of this integrated approach, it is applied to study the damage behaviour of aerospace carbon/epoxy composite laminates with an open hole, subjected to quasi-static tension and fatigue at a load ratio of 1:10. The study also explores the applicability of a Paris law type relationship to determine effective macroscopic fatigue delamination resistance in the load-bearing plies. The X-ray imaging for both load cases revealed extensive formation of delaminated fracture surfaces surrounding both glass fibre interlacing weaves and entrained voids within them, acting as preferential sites for localised strain hot spots. It is demonstrated that local energy dissipation is governed by the recurring weave pattern and topological order, which can help explain the typical damage state in quasi-static behaviour, establishing a direct link between microstructural features and macrostructural material response. Full article

To improve the operational efficiency of the park source-load-storage system and reduce operation costs and the wind-solar curtailment rate, this paper establishes a Park Integrated Energy System (PIES) model with multiple energy storage and vehicle-to-grid (V2G) components and proposes an adaptive comprehensive fitness multi-objective particle swarm optimization algorithm. First, each component of the PIES is modeled. Second, electric vehicle (EV) scheduling boundaries, determined by wind and PV output, as well as a dynamic charging-discharging incentive mechanism, are designed to enhance renewable energy accommodation. Finally, an adaptive comprehensive fitness index is defined, and convergence and particle-update strategies are improved to achieve better scheduling performance. Simulation results verify that the proposed PIES model achieves optimal performance in terms of carbon-emission cost, total operation cost, and wind-solar curtailment rate. Meanwhile, the improved algorithm also outperforms traditional multi-objective methods in PIES scheduling. Full article

The global energy transition toward decarbonization and digitalization is profoundly reshaping modern power systems. Smart grids and microgrids have become core enabling technologies for accommodating high-penetration renewable energy, facilitating flexible source–load interaction, and enhancing system efficiency, reliability, and resilience. Based on the Special Issue “Advances in Smart Grids and Microgrids: Distributed Generation and Energy Storage Systems” and recent state-of-the-art progress, this paper systematically reviews key research advances in four core areas: planning and design paradigms, operation optimization and control under uncertainty, economic and market mechanism design, and resilience and cyber–physical security. Emphasis is placed on the synergistic optimization between distributed renewable generation and advanced energy storage (ES) systems in both single-energy and multi-energy architectures. Typical applications in urban areas, remote islands, and hardware-in-the-loop validation are summarized. Furthermore, major challenges and future trends are highlighted, including cross-scale interoperability, resilient control, cyber–physical security, advanced ES, electricity–carbon integrated markets, and so on. It is demonstrated that the transition from deterministic centralized frameworks to stochastic distributed multi-energy integrated systems has become an inevitable trend, and interdisciplinary collaboration will further promote the development of clean, resilient, cost-effective, and equitable smart grids and microgrids. Full article

The low-carbon transition of the power sector is fundamental to achieving “Dual Carbon” goals, where demand-side management plays an increasingly vital role in transforming flexible loads into renewable energy accommodation and active emission-reduction resources. However, existing low-carbon demand response mechanisms based on dynamic carbon emission factors only reflect average system states and fail to quantify the incremental carbon impact of marginal load changes. To address this limitation, this paper proposes a novel marginal carbon emission factor-driven low carbon demand response mechanism. Unlike traditional methods, the proposed mechanism utilizes marginal carbon emission factors as a high-sensitivity guiding signal to inform users of the real-time emission and renewable energy consumption variations caused by their consumption adjustments. Furthermore, considering the forecasting errors of high-penetration renewable energy, the uncertainty of marginal carbon emission factors is explicitly considered. Case studies are conducted to compare the proposed method with the conventional method through comparative analyses based on the modified PJM-5 system. Results demonstrate that the MCEF-driven approach provides more precise carbon-reduction and renewable energy utilization signals to achieve superior system-wide decarbonization performance and sustainable development. Full article

Textile wastewater is among the most challenging industrial effluents due to its complex composition, high pollutant load, and low biodegradability. Conventional treatment methods often fall short in achieving complete removal of dyes and emerging contaminants. Photocatalytic composite membranes have emerged as a promising solution by integrating membrane separation and advanced oxidation processes. This review provides a comprehensive overview of the design, fabrication, and performance of photocatalytic composite membranes for textile wastewater treatment. Key aspects include the types of photocatalysts employed, methods of incorporation into membranes, and their synergistic role in pollutant removal and membrane fouling mitigation. Recent advancements in materials science, such as visible-light-responsive catalysts, carbon-based nanocomposites, and self-cleaning surfaces, are discussed, along with current limitations related to catalyst stability, operational scalability, and cost. This review underscores the potential of photocatalytic composite membranes as a next-generation platform for sustainable and effective textile wastewater treatment. Full article